Singularity Container Workflow Part 5: Running the Tensorflow container in WSL2
Now that we have readied the WSL2 environment with Singularity and the relevant CUDA libraries, it’s time to run the sample Keras workflow.
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Singularity Container Workflow: Part 4 – Signing the Container
Signing the Container The Singularity 3.0 family introduced the ability to create (and manage) PGP keys to sign and verify containers. This provides a trusted method for Singularity users to share containers and ensures a bit-for-bit reproduction of the original...
Supporting Local Files in a Singularity Remote Build
Overview This long awaited feature allows copying local files into remote builds via the %files section of the Singularity def file the same way as you would if you were building locally with singularity build. No special command-line arguments or other user actions...
CUDA GPU Containers on Windows with WSL2
Version 2 of the Microsoft Windows Subsystem for Linux (WSL2) now supports GPU computing with CUDA. With the --nvccli functionality introduced in Singularity 3.9 you can now run GPU containers with SingularityCE or SingularityPRO on your Windows system that has a...
Introducing HPC Affinities to the Enterprise: A New Open Source Project Integrates Singularity and Slurm via Kubernetes
TL;DR: “slurm-operator,” a new open source project, allows workload containerized by Singularity to be managed in one or more Slurm clusters directly from Kubernetes; the net result is a fully converged infrastructure for hybrid use cases involving a blend of services...
Update to examples – November 9
Sylabs continues to provide example Singularity containers. Our latest installment of updates is as follows: ContikiOSContiki is an open source operating system that runs on tiny low-power microcontrollers and makes it possible to develop applications that make...
Update to examples – October 2
Here are a few more Singularity containers, that we at Sylabs have put together: CaffeCaffe is a Deep Learning framework. https://github.com/sylabs/examples/tree/master/machinelearning/caffeSingularity Definition File HorovodHorovod is a distributed-training framework...
Spark on Singularity
Apache Spark is a fast, in-memory data processing engine applicable to large-scale data processing, for both batch and streaming machine learning that requires fast access to data sets. Apache Spark’s run-everywhere ethos is now taken a few steps further with the BYOE...